The advent of global communications networks supplies users with access to significant amount of data. In general, such free flow of information prevalent today in wired and wireless regimes demands that the source and destination be compatible insofar as storing and interpreting the data for use, for example. The world is populated with information sources where in many cases the data can be represented differently from source to source.
Accordingly, a major challenge facing companies and individuals today is that data existing in one model/schema may be needed in a different model/schema for another purpose. Conversion processes are being hampered by a largely disparate and ever-changing set of models/schemas. For example, in data warehousing where data is received from many different sources for storage and quick access from other sources, conversion processes can create difficulties. Converting data from one model to another model is not only time-consuming and resource intensive, but can be fraught with conversion problems.
Furthermore, conventional data systems, applications and operating systems have typically relied on multiple incompatible handling and exchange for data, including; the registry, event log messages, contact information, and e-mail—or simply have used multiple flat files for data such as images and audio. For example, in conventional data stores, stored contents are in general treated as separate entities, even though they are interrelated at some level. Accordingly, when a large number of items and applications exist, it can become important to have a flexible and efficient mechanism to exchange items between applications.
At the same time, given new file systems that operate based on relational objects with an extensible data type, new challenges can arise. For example, in such environments, a data model can play an important role in the way that participants interact with the database. Moreover, a manner for which applications exchange, store and retrieve data can be governed by the data model.
Interactions involved with data handling of such a data store can involve various parties and different data models. Accordingly, existence of different models can hinder proper interaction between the participants, as data may not be properly representable to all parties involved. Moreover, conventional methods of converting from one data representation to another can typically become time consuming and resource intensive, while at the same time be fraught with conversion problems, and in some cases, totally impracticable due to such complexity.
As programming approaches and foundations have evolved, application programming interfaces (APIs) and programming schemas have been developed to standardize and unify programming methodologies that were previously multi-variant and relatively incompatible. Modern programming therefore often involves employing APIs and schemas in conjunction with reusable libraries. Such Programming languages continue to evolve to facilitate specification by programmers as well as efficient execution.
Compilers and/or interpreters bear the burden of translating high-level logic into executable machine code. In general, compilers and/or interpreters are components that receive a program specified in a source programming language (e.g., C C#, Visual Basic, Java . . . ) and covert the logic provided thereby to machine language that is executable by a hardware device.
However, the conversion need not be done verbatim. In fact, conventional compilers and/or interpreters analyze the source code and generate very efficient code. For example, programmers write code that sets forth a logical flow of operations that is intuitive and easy for humans to understand, but is often inefficient for a computer to execute. Compilers and/or interpreters can identify inefficiencies and improve program performance at the hardware level by eliminating unnecessary operations and/or rearranging the execution of instructions while still achieving the intended results. In this manner, programmers can create robust and efficient software.